Advanced Certificate in Applied Automation in the Digital Economy Module 4: Data Analytics for Automation Decision Making
- Analytics & Tech
- Finance & Investment
- Innovation & Business Improvement
This module is conducted in-person.
2 Full Days (Weekdays)
Who Should Attend
- Professionals across industries aiming to utilise data analytics for informed decision-making and automation initiatives, including business analysts, data scientists, automation engineers, project managers, and IT professionals.
PREREQUISITES
There are no prerequisites for this programme. Prior knowledge on any of the topics is not required.
Overview
This module is designed to equip participants with the knowledge and skills required to leverage data analytics in making informed decisions within an automated environment. Key topics include an introduction to data analytics fundamentals, data visualisation techniques for deriving meaningful insights, the application of machine learning algorithms for automated decision-making, predictive modeling and forecasting methodologies using advanced statistical tools, and ethical considerations surrounding data-driven decision-making processes. At the end of the module, participants will gain essential competencies to utilise data analytics effectively within automated systems. This will empower them to make informed decisions, thereby fostering efficiency and innovation in digital economies.
Learning Objectives
At the end of the 2-day module, participants will be able to:
- Understand the fundamental principles of data analytics and its role in automation decision making within the context of digital economy
- Develop proficiency in using relevant data analytics tools and techniques to analyse large datasets for identifying patterns, trends, and insights that can inform automation decision making
- Demonstrate the ability to apply statistical methods and machine learning algorithms to derive actionable conclusions from data for optimising automated processes in a digital economy setting
- Evaluate the ethical considerations and potential biases associated with utilising data analytics for automation decision making, and propose strategies to mitigate these challenges
- Design and implement a comprehensive data-driven approach to automate decision-making processes within a digital economy framework, considering factors such as scalability, reliability, and adaptability
Assessment
As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.
Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$654 (After SSG Funding 70%) |
$254 (After SSG Funding 70% |
$654 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
|
International Participant |
$2,180 (No Funding) |
$2,180 (No Funding) |
$2,180 (No Funding) |
All prices include 9% GST
Please note that the programme fees are subject to change without prior notice.
Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.
Self Sponsored
SkillsFuture Credit
Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.
This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.
Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).Workfare Skills Support Scheme
From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.
Company Sponsored
Enhanced Training Support for SMEs (ETSS)
- Organisation must be registered or incorporated in Singapore
- Employment size of not more than 200 or with annual sales turnover of not more than $100 million
- Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
- Trainees must be Singapore Citizens or Singapore Permanent Residents
- Trainees must not be a full-time national serviceman
- Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here.
Please click here for more information on ETSS.
Absentee Payroll
Companies who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:
AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)
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